About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
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Convert a scalar value to a zero-dimensional ndarray.
npm install @stdlib/ndarray-base-from-scalar8000 Alternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var scalar2ndarray = require( '@stdlib/ndarray-base-from-scalar' );Returns a zero-dimensional ndarray containing a provided scalar value and having a specified data type.
var x = scalar2ndarray( 1.0, 'float64', 'row-major' );
// returns <ndarray>
var sh = x.shape;
// returns []
var dt = x.dtype;
// returns 'float64'
var v = x.get();
// returns 1.0var dtypes = require( '@stdlib/ndarray-dtypes' );
var scalar2ndarray = require( '@stdlib/ndarray-base-from-scalar' );
// Get a list of data types:
var dt = dtypes();
// Generate zero-dimensional arrays...
var x;
var i;
for ( i = 0; i < dt.length; i++ ) {
x = scalar2ndarray( i, dt[ i ], 'row-major' );
console.log( x.get() );
}@stdlib/ndarray-array: multidimensional arrays.@stdlib/ndarray-base/ctor: base multidimensional array.@stdlib/ndarray-ctor: multidimensional array constructor.
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.
